In this paper, I derive a structural econometric model of learning by doing from a dynamic oligopoly game. Unlike previous empirical models, this model is capable of testing hypotheses concerning both the technological nature and behavioral implications of learning. I estimate the model with firm level data from the early U.S. rayon industry. The empirical results show that there were considerable differences across firms in both proprietary and spillover learning. The results also indicate that two of the three firms took their rival's reactions into account when choosing their strategies.
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Asymmetric Learning Spillovers
April 1993
Working Paper Number:
CES-93-07
In this paper, I employ a linear-quadratic model of an industry characterized by learning by doing to examine the implications of asymmetric learning spillovers. Importantly, I show that distribution of spillover benefits can influence market structure in ways that can not be seen in models where spillovers are symmetric. If spillovers are asymmetric, a tradeoff between improved industry performance and increased market concentration can arise which does not occur when they are symmetric. This tradeoff leads to a policy dilemma; whether to promote static or dynamic efficiency in markets where learning is important.
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Learning by Doing and Plant Characteristics
August 1996
Working Paper Number:
CES-96-05
Learning by doing, especially spillover learning, has received much attention lately in models of industry evolution and economic growth. The predictions of these models depend on the distribution of learning abilities and knowledge flows across firms and countries. However, the empirical literature provides little guidance on these issues. In this paper, I use plant level data on a sample of entrants in SIC 38, Instruments, to examine the characteristics associated with both proprietary and spillover learning by doing. The plant level data permit tests for the relative importance of within and between firm spillovers. I include both formal knowledge, obtained through R&D expenditures, and informal knowledge, obtained through learning by doing, in a production function framework. I allow the speed of learning to vary across plants according to characteristics such as R&D intensity, wages, and the skill mix. The results suggest that (a) Ainformal@ knowledge, accumulated through production experience at the plant, is a much more important source of productivity growth for these plants than is Aformal@ knowledge gained via research and development expenditures, (b) interfirm spillovers are stronger than intrafirm spillovers, (c) the slope of the own learning curve is positively related to worker quality, (d) the slope of the spillover learning curve is positively related to the skill mix at plants, (e) neither own nor spillover learning curve slopes are related to R&D intensities. These results imply that learning by doing may be, to some extent, an endogenous phenomenon at these plants. Thus, models of industry evolution that incorporate learning by doing may need to be revised. The results are also broadly consistent with the recent growth models.
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Innovation and Regulation in the Pesticide Industry
December 1995
Working Paper Number:
CES-95-14
This paper examines the hypothesis that regulation negatively affects pesticide innovation, causes pesticide companies to introduce more harmful pesticides, and discourages firms from developing pesticides for minor crop markets. The results confirm that pesticide regulation adversely affects innovation and discourages firms from developing pesticides for minor crop markets. Contrary to the hypothesis, however, regulation encourages firms to develop less toxic pesticides. Estimates suggest that it requires about $29 million in industry expenditures on health and environmental testing to affect the toxicity of one new pesticide.
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Industry Learning Environments and the Heterogeneity of Firm Performance
December 2006
Working Paper Number:
CES-06-29
This paper characterizes inter-industry heterogeneity in rates of learning-by-doing and examines how industry learning rates are connected with firm performance. Using data from the Census Bureau and Compustat, we measure the industry learning rate as the coefficient on cumulative output in a production function. We find that learning rates vary considerably among industries and are higher in industries with greater R&D, advertising, and capital intensity. More importantly, we find that higher rates of learning are associated with wider dispersion of Tobin's q and profitability among firms in the industry. Together, these findings suggest that learning intensity represents an important characteristic of the industry environment.
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Regulation and Firm Size, Foreign-Based Company Market Presence, Merger Choice In The U.S. Pesticide Industry
June 1994
Working Paper Number:
CES-94-06
This paper uses Two-Stage Least Squares to examine the impact of pesticide product regulation on the number of firms and the foreign-based company market share of U.S. Pesticide Companies. It also investigates merger choice with a multinomial logit model. The principal finding is that greater research and regulatory costs affected small innovative pesticide companies more than large ones and encouraged foreign company expansion in the U.S. pesticide market. It was also found that the stage of the industry growth cycle and farm sector demand influenced the number of innovative companies and foreign-based company market share. Finally, firms that remain in the industry were found to have greater price cost margins, lower regulatory penalties costs, and a much greater multinational business presence than those that departed.
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Import Price Pressure on Firm Productivity and Employment: The Case of U.S. Textiles
March 2006
Working Paper Number:
CES-06-09
Theoretical research has predicted three different effects of increased import competition on plant-level behavior: reduced domestic production and sales, improving average efficiency of plants, and increased exit of marginal firms. In empirical work, though, such effects are difficult to separate from the impact of exogenous technological progress (or regress). I use detailed plant-level information available in the US Census of Manufacturers and the Annual Survey of Manufacturers for the period 1983-2000 to decompose these effects. I derive the relative contribution of technology and import competition to the increase in productivity and the decline in employment in textiles production in the US in recent years. I then simulate the impact of removal of quota protection on the scale of operation of the average plant and the incentive to plant closure. The methodology employs a number of important innovations in examining the impact of falling import prices on the domestic production of an import-competing good. First, import competition is modeled directly through its impact on the relative prices of monopolistically competitive goods along the lines suggested by Melitz (2000). Second, the effect of technology is incorporated through structural estimation of plant-level production functions in four factors (capital, labor, energy and materials). Solutions to econometric difficulties related to missing capital data and unobserved productivity are incorporated into the estimation technique. The model is estimated for plants with primary product in SIC 2211 (broadwoven cotton cloth). Results validate modeling demand as for differentiated products. Technological coefficients are sensible, with exogenous technological progress playing a large role. In the simulations run, the effects of foreign price competition are orders of magnitude higher than those of technological progress for the period after quotas on imports are removed. The large-scale reduction in employment and output in the US is shown to be a combination of reduced employment and output at plants in continuous operation and of plant closures that exceed new entries.
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The Survival of Industrial Plants
October 2002
Working Paper Number:
CES-02-25
The study seeks to explain the attrition rate of new manufacturing plants in the United States in terms of three vectors of variables. The first explains how survival of the fittest proceeds through learning by firms (plants) about their own relative efficiency. The second explains how efficiency systematically changes over time and what augments or diminishes it. The third captures the opportunity cost of resources employed in a plant. The model is tested using maximum-likelihood probit analysis with very large samples for successive census years in the 1967-97 period. One sample consists of an unbalanced panel of about three-fourths of a million plants of single and multi-unit firms, or alternatively of about 300,000 plants if only the most reliable data are considered. The second is restricted to the plants of multi-unit firms in the same time span and consists of an unbalanced panel of more than 100,000 plants. The empirical analysis strongly confirms the predictions of the model.
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The Dynamics of Market Structure and Market Size in Two Health Services Industries
October 2007
Working Paper Number:
CES-07-26
The relationship between the size of a market and the competitiveness of the market has been of long-standing interest to IO economists. Empirical studies have used the relationship between the size of the geographic market and both the number of firms in the market and the average sales of the firms to draw inferences about the degree of competition in the market. This paper extends this framework to incorporate the analysis of entry and exit flows. A key implication of recent entry and exit models is that current market structure will likely depend upon history of past participation. The paper explores these issues empirically by examining producer dynamics for two health service industries, dentistry and chiropractic services. We find that the number of potential entrants and past number of incumbent firms are correlated with current market structure. The empirical results also show that as market size increases the number of firms rises less than proportionately, firm size increases, and average productivity increases. However, the magnitude of the correlations are sensitive to the inclusion of the market history variables.
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R&D Reactions To High-Technology Import Competition
March 1991
Working Paper Number:
CES-91-02
For a seventeen-year panel covering 308 U.S. manufacturing corporations, we analyze firms' R&D spending reactions to changes in high-technology imports. On average, companies reduced their R&D/sales ratios in the short run as imports rose. Individual company reactions were heterogeneous, especially for multinational firms. Short-run reactions were more aggressive (i.e., tending toward R&D/sales ratio increases), the more concentrated the markets were in which the companies operated, the larger the company was, and the more diversified the firm's sales mix was. Reactions were less aggressive when special trade barriers had been erected or patent protection was strong in the impacted industries. Companies with a top executive officer educated in science or engineering were more likely to increase R&D/sales ratios in response to an import shock, all else equal. Over the full 17-year sample period, reactions may have shifted toward greater average aggressiveness.
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"It's Not You, It's Me": Breakup In U.S.-China Trade Relationships
February 2014
Working Paper Number:
CES-14-08
This paper uses confidential U.S. Customs data on U.S. importers and their Chinese exporters toinvestigate the frictions from changing exporting partners. High costs from switching partners can affect the efficiency of buyer-supplier matches by impeding the movement of importers from high to lower cost exporters. I test the significance of this channel using U.S. import data, which identifies firms on both sides (U.S. and foreign) of an international trade relationship, the location of the foreign supplier, and values and quantities for the universe of U.S. import transactions. Using transactions with China from 2003-2008, I find evidence suggesting that barriers to switching exporters are considerable: 45% of arm's-length importers maintain their partner from one year to the next, and one-third of all switching importers remain in the same city as their original partner. In addition, importers paying the highest prices are the most likely to change their exporting partner. Guided by these empirical regularities, I propose and structurally estimate a dynamic discrete choice model of exporter choice, embedded in a heterogeneous firm model of international trade. In the model, importing firms choose a future partner using information for each choice, but are subject to partner and location-specific costs if they decide to switch their current partner. Structural estimates of switching costs are large, and heterogeneous across industries. For the random sample of 50 industries I use, halving switching costs shrinks the fraction of importers remaining with their partner from 57% to 18%, and this improvement in match efficiency leads to a 12.5% decrease in the U.S.-China Import Price Index.
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